Morphological granulometries and their moment features are used as shape descriptors. These features find application in classification, segmentation and estimation. Design of classifiers has been a primary goal of most pattern recognition problems. Small sample design is often a constraint when designing classifiers. We use a recently proposed small sample design method in which the sample observations are spread with a probability mass and the classifiers designed on the spread mass. The designed classifiers are more reliability for relative to the population. Two issues are addressed: design of granulometric classifiers using a small sample, and granulometric classification based on a very small number of features.

Date Published: 22 May 2002
PDF: 8 pages
Proc. SPIE 4667, Image Processing: Algorithms and Systems, (22 May 2002); doi: 10.1117/12.467971

Published in SPIE Proceedings Vol. 4667:
Image Processing: Algorithms and Systems
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)